This chapter will provide an overview of how citizen science has contributed to the development of remotely sensed land cover and land use maps in the form of training and validation data collection using visual interpretation and field-based data collection methods. Online visual interpretation via applications such as Geo-Wiki and Collect Earth as well as in situ data collection via mobile apps are now yielding vast quantities of data that are benefiting remote sensing applications. Existing citizen-driven initiatives such as OpenStreetMap are also providing input data for generating land cover and land use maps while data quality remains a key area of concern regarding the use of citizen-generated data.